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Araceli Queirolo Córdova

dblp:348/9023 · DBLP profile ↗
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2ranked-venue papers
0as first author
2since 2021 · last 2024
0009-0007-5042-7044ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 2 · 2 since 2021Human-computer interaction and ubiquitous computing · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Software engineering, system software, and programming languages
1 paper
Empirical software engineering · 50% Program analysis · 50%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Empirical software engineering
developer studies
0.812024
Asking and Answering Questions During Memory Profiling · IEEE Trans. Software Eng. 2024
Program analysis › dynamic analysis
memory profiling
0.812024
Asking and Answering Questions During Memory Profiling · IEEE Trans. Software Eng. 2024

Methods — techniques the papers use, named apart from their topics

observation · 0.8interviews · 0.8exploratory study · 0.8
YearPublicationVenuePosition
2024 Asking and Answering Questions During Memory Profiling
abstract
The software engineering community has produced numerous tools, techniques, and methodologies for practitioners to analyze and optimize memory usage during software execution. However, little is known about the actual needs of programmers when analyzing memory behavior and how they use tools to address those needs. We conducted an exploratory study (i) to understand what a programmer needs to know when analyzing memory behavior and (ii) how a programmer finds that information with current tools. From our observations, we provide a catalog of 34 questions programmers ask themselves when analyzing memory behavior. We also report a detailed analysis of how some tools are used to answer these questions and the difficulties participants face during the process. Finally, we present four recommendations to guide researchers and developers in designing, evaluating, and improving memory behavior analysis tools.
Alison Fernandez, Araceli Queirolo Córdova, Alexandre Bergel, Juan Pablo Sandoval Alcocer
IEEE Trans. Software Eng.2
2022 Visualizing Memory Consumption with Vismep
abstract
Detecting and repairing memory issues is still a challenging task. One reason is that understanding a program's memory usage involves a diverse and related set of dynamic and static aspects. Over the years, multiple tools have been proposed to assist practitioners in these activities. However, detailed information about how a tool helps users when analyzing memory usage is missing.This article introduces Vismep, an interactive visualization prototype to help programmers analyze Python applications' memory usage, and presents an exploratory study to understand the behavior and perception of users when using Vismep. As a result, we reported five information needs when participants analyze memory consumption and how they use Vismep to satisfy these needs. Besides, participants positively perceived Vismep due to their valuable views and high overall usability.
Alison Fernandez, Alexandre Bergel, Juan Pablo Sandoval Alcocer, Araceli Queirolo Córdova
VISSOFT4